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intermezzo672/NHS-pubmedbert

sourceHugging Facemitupdated 3y agoView on Hugging Face
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Model Card

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NHS-pubmedbert

This model is a fine-tuned version of microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6667
  • Accuracy: 0.8177
  • Precision: 0.8190
  • Recall: 0.8177
  • F1: 0.8143

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 3e-05
  • trainbatchsize: 16
  • evalbatchsize: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • num_epochs: 6

Training results

Training LossEpochStepValidation LossAccuracyPrecisionRecallF1
0.08271.03970.43850.79940.81280.79940.8011
0.01492.07940.44840.82270.82320.82270.8229
0.00273.011910.66670.81770.81900.81770.8143

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.15.0
  • Tokenizers 0.15.0